• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.348-359
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• 2017

Recently, various public transportation activation policies are being implemented in order to mitigate traffic congestion in metropolitan areas. Especially in the metropolitan area, the bus information system has been introduced to provide information on the current location of the bus and the estimated arrival time. However, it is difficult to predict the travel time due to repetitive traffic congestion in buses passing through complex urban areas due to repetitive traffic congestion and bus bunching. The previous bus travel time study has difficulties in providing information on route travel time of bus users and information on long-term travel time due to short-term travel time prediction based on the data-driven method. In this study, the path based long-term bus travel time prediction methodology is studied. For this purpose, the training data is composed of 2015 bus travel information and the 2016 data are composed of verification data. We analyze bus travel information and factors affecting bus travel time were classified into departure time, day of week, and weather factors. These factors were used into clusters with similar patterns using self organizing map. Based on the derived clusters, the reference table for bus travel time by day and departure time for sunny and rainy days were constructed. The accuracy of bus travel time derived from this study was verified using the verification data. It is expected that the prediction algorithm of this paper could overcome the limitation of the existing intuitive and empirical approach, and it is possible to improve bus user satisfaction and to establish flexible public transportation policy by improving prediction accuracy.

• Journal of Korea Spatial Information System Society
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• v.10 no.3
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• pp.31-43
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• 2008

Travel time prediction is an indispensable to many advanced traveler information systems(ATIS) and intelligent transportation systems(ITS). In this paper we propose a method to predict travel time using $Na{\ddot{i}}ve$ Bayesian classification method which has exhibited high accuracy and processing speed when applied to classily large amounts of data. Our proposed prediction algorithm is also scalable to road networks with arbitrary travel routes. For a given route, we consider time-varying average segment velocity to perform more accuracy of travel time prediction. We compare the proposed method with the existing prediction algorithms like link-based prediction algorithm [1] and Micro T* algorithm [2]. It is shown from the performance comparison that the proposed predictor can reduce MARE (mean absolute relative error) significantly, compared with the existing predictors.

• Journal of Korean Society of Transportation
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• v.34 no.6
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• pp.570-579
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• 2016

This study proposes a concept of Stepwise Transfer Coefficient(STC) which implies greater transfer cost with increasing the number of transfers. Thus, the public transport information system provides the choice sets of travel routes by the consideration of not only transportation time but also the optimum number of transfers. However, path choice problems that involve STC are found to include non additive cost, which requires additional route enumeration works. Discussions on route enumeration in actual transportation networks is very complicated, thereby warranting a theoretical examination of route search considering STC. From these points of view, this study results in a probability based transit trip assignment model including STC. This research also uses incoming link based entire route deletion method. The entire route deletion method proposed herein simplifies construction of an aggregation of possible routes by theoretically supporting the process of enumeration of the different routes from origin to destination. Conclusively, the STC reflected route based logit model is proposed as a public transportation transit trip assignment model.

• IE interfaces
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• v.17 no.spc
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• pp.103-110
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• 2004

This paper presents a two-phase method for the vehicle routing problems with time windows(VRPTW). In a supply chain management(SCM) environment, timely distribution is very important problem faced by most industries. The VRPTW is associated with SCM for each customer to be constrained the time of service. In the VRPTW, the objective is to design the least total travel time routes for a fleet of identical capacitated vehicles to service geographically scattered customers with pre-specified service time windows. The proposed approach is based on ant colony optimization(ACO) and improvement heuristic. In the first phase, an insertion based ACO is introduced for the route construction and its solutions is improved by an iterative random local search in the second phase. Experimental results show that the proposed two-phase method obtains very good solutions with respect to total travel time minimization.

• Journal of Korean Society of Transportation
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• v.13 no.1
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• pp.95-110
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• 1995

n this research neural -based model was developed to forecast link travel times , And it is also compared wiht other time series forecasting models such as Box-Jenkins model, Kalman filter model. These models are validated to evaluate the accuracy of models with real time series data gathered by the license plate method. Neural network's convergency and generalization were investigated by modifying learning rate, momentum term and the number of hidden layer units. Through this experiment, the optimum configuration of the nerual network architecture was determined. Optimumlearining rate, momentum term and the number of hidden layer units hsow 0.3, 0.5, 13 respectively. It may be applied to DRGS(dynamic route guidance system) with a minor modification. The methods are suggested at the condlusion of this paper, And there is no doubt that this neural -based model can be applied to many other itme series forecating problem such as populationforecasting vehicel volume forecasting et .

• Proceeding of EDISON Challenge
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• 2015.03a
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• pp.479-483
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• 2015

In case of the big city, choosing the adequate root of which we can reach the destination can affect the driver's condition and driving time. so it is quite important to find the optimal routes for arriving the destination as considering the factors, such as driving conditions or travel time and so on. In this paper, we develop route choice model with considering driving conditions and travel time, and it can search the optimal path which make drivers reduce their fatigues using genetic algorithm.

• Acta Via Serica
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• v.8 no.1
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• pp.55-70
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• 2023

Carpets are a useful tool for highlighting the cultural uniqueness of a region because their characteristic usage often reveals distinctive natural features of the place or the unique cultural identity of a group. Investigating anecdotes and associated patterns found in three medieval trans-Eurasian travelogues, this paper focuses on observations made by the Chinese Buddhist monk, Faxian, the Sunni pilgrim and scholar, Ibn Battuta, and Marco Polo, the Venetian merchant examining their thoughts, observations, and perspectives on carpet-related customs in their experienced contexts. In particular, this manuscript touches on the controversies, impacts, and narratives associated with carpet practices observed in each travel writer's context respectively, concluding that each traveler shows several things in common rather than showing different patterns depending on the characteristics of their religion. Overall, they observed the uses of carpets according to their jobs and travel purposes and appropriately detailed related episodes if the intended purpose and context matched the uses.

• Proceedings of the KOR-KST Conference
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• 1995.05b
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• pp.69-76
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• 1995

Difficulties in riding , driving and parking are a common issue which inevitably appears in city urbanization and city modernization development all over the world. However, those cities differ in controlling the traffic. According to the specific practice in Shanghai, this article presents the various factors which affect the traffic capacity and operation quality . This article also outlines transportation system management technique of overall coordination and comprehensive control in the following seven aspects : controlling traffic motivation : improving traffic distribution : reasonably and scientifically selecting travel mode, travel route and travel time : reinforcing traffic management and road construction. The article finally suggests that the above mentioned points are cost-effective ways of the handling traffic plight for metropolitan transport.

• Proceedings of the KOR-KST Conference
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• 1995.05a
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• pp.61-68
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• 1995

Difficulties in riding, driving and parking are a common issue which inevitably appears in city urbanization and city modernization development all over the world. However, those cities differ in controlling the traffic. According to the specific practice in Shanghai, this article presents the various factors which affect the traffic capacity and the operation quality. This article also outlines transportation system management technique of overall coordination and comprehensive control in the following seven aspects: controlling traffic motivation; improving traffic distribution; reasonably and scientifically selecting travel mode, travel route and travel time; reinforcing traffic management and road construction. The article finally suggests that above mentioned points are cost-effective ways of handling traffic plight for metropolitan transport.

• Journal of Environmental Impact Assessment
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• v.20 no.2
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• pp.217-226
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• 2011

This paper was inspired by the fact that Real-time Traffic Information Service could play a key role in reducing incomplete combustion time remarkably since it can provide traffic jam information in real-time basis. Emission characteristics of experimental engines were studied with variable travel distances and speed of car in terms of traffic information provided. 12 Km distance road of Susung district in Daegu is taken as an experimental area to examine this new approach. The emission was tested while the driving was done at 8 AM, 3 PM, 6 PM which represents various traffic conditions. The reduced emission has been measured for a travel distance running at different loads (conventional shortest route and Real-time Traffic Information) and various loads (CO, VOC and NOx) are all inventoried and calculated in terms of existing emission factors. The emission has been shown to reduce linearly with travel distance : carbon monoxide (20.56%), VOC (29.21%), NOx(8.86%).